Aim. To study the possibilities and limitations of the social network as a digital medical tool, which is aimed at improving programs for primary and secondary stroke prevention in young people.Material and methods. The study was carried out in the format of online training for volunteers. At the first stage of the work, the online school “Stroke in Young People” was announced in 8 medical blogs. As part of the school, a special account was created for readers (n=1354). At the second stage, 49 respondents (4% of men, whose average age was 24.4±5.2 years) were selected from 1354 listeners, who were surveyed on “Awareness of risk factors and stroke symptoms among users of social networks” before and after the online school.Results. The online school audience is predominantly female (91%), and 43% of readers were in the 25-34 age group. The total number of people who listened to and read the online school material is 8712 people. 17% worked in the healthcare system, and 22% of respondents had a history of stroke. 38 (78%) people of the 2nd stage among the respondents independently searched for information about stroke earlier, and 30 (61%) received this information passively from medical workers in 2020. Before the online school start, the majority of respondents (over 60%) were aware of 2 out of 7 stroke risk factors (dyslipidemia and arterial hypertension) and 3 out of 6 stroke signs (drooping of the face half, weakness in the limbs and difficulty speaking). Less than 40% of the participants considered the stroke risk factors for diabetes mellitus, other cardiovascular diseases (CVD), obesity, and alcohol use; less than 20% were aware of stroke symptoms such as impaired vision and coordination and very severe headache. After completing online learning, the greatest increase in knowledge was found among the following risk factors – smoking and other CVDs (p<0.05); stroke symptoms - headache and drooping of the face half (p<0.05).Conclusion. The online school aroused interest among healthcare workers and people without medical education, including those with stroke. Most of the respondents believed that they knew how to prevent a stroke (over 80%) and would be able to provide first aid to a person with a stroke (over 90%). At the same time, the awareness of risk factors and stroke symptoms was low prior to the start of learning, even though the study included healthcare workers and stroke survivors. Online learning has led to increased awareness of some risk factors and stroke symptoms. Social media can be one of the tools for medical prevention of stroke in young people, but program planning should take into account the way the material is presented and its readability.
Funding Acknowledgements Type of funding sources: None. Purpose. To study the potential of Instagram as a hosting platform for an online school in order to improve the programmes of primary prevention of stroke in young people. Material and methods. At the first stage of the study, October 2020, the ‘Stroke in the Young’ online school was announced on 8 medical blogs. For the online school a special account was created under insult.u.molodjh (1,354 followers). As part of the online school are 8 posts and 6 open online lectures. At the second stage, to study the effectiveness of the online school, 50 respondents (4% male, mean age 24.4 ± 5.2 years) were selected from 1,354 students by an electronic random number generator and asked to fill in the questionnaire on ‘Awareness of Risk Factors (RF) and Symptoms of Stroke Among Social Network Users’ before and after the school completion. Results. The total number of people who listened to and read the material of the online school is 8,712 people; the overall engagement is 470 people. 48% of the respondents of the 2nd stage were 18 to 44 years old; 76% of the respondents had post-secondary education. Of the respondents, 16% were employed in the healthcare system and 22% had a history of stroke, 76% had independently searched for information on stroke earlier and 60% received this information passively from healthcare professionals in 2020. The most significant parameters affecting awareness of stroke RF were employment in the healthcare system (alcohol consumption, OR 0.186, CI 0.043–0.804, p = 0.02; high blood pressure (BP), OR 14.945, CI 0.959–233.012, p = 0.05); getting informed about stroke in 2020 (cardiovascular diseases (CVD), OR 3.561, CI 1.093–11.605, p = 0.03; obesity, OR 3.044, CI 1.011–9.163, p = 0.04) and post-secondary education (high BP, OR 6.001, CI 0.920–39.136, p = 0.06; CVD, OR 0.268, CI 1.093–11.605, p = 0.03). Factors that affected the awareness of individual stroke symptoms were getting informed about stroke in 2020 (p = 0.02), education (p = 0.005), history of strokes (p = 0.01) and employment in the healthcare system (p = 0.05). When the questionnaire was completed again after training, it was shown that the online training leads to better chances of improving health literacy with respect to a number of RF (cholesterol awareness (OR 4.6, CI 1.1–18.7), smoking as a risk factor for stroke (OR 3.3, CI 1.3–8.1)) and stroke symptoms (face drooping, OR 5.1, CI 1.0–27.4; very severe headache, OR 3.1, CI 1.0–9.4). Conclusions. Instagram can be used to host online schools in order to improve programmes for primary prevention of stroke in young people. The online school has aroused interest among both healthcare professionals and people without medical education, including those with a history of stroke. Online training led to better chances of improving health literacy with respect to a number of RF, such as awareness of high cholesterol and smoking, and contributed to improving health literacy for such stroke symptoms as face drooping and very severe headache.
Purpose: To determine the most effective methods of informing people about the primary prevention of hypertension using a social media website. Materials and methods: It was a randomized, prospective, two-stage study conducted on a social media website (i.e., the Instagram platform). At Stage 1 Save Your Heart online school was announced, and 945 applicants were registered for the training. The online training programme included the following modules: Risk Factors for Cardiovascular Diseases (CVDs), Heart-Healthy Diet, Cholesterol. What a Patient Needs to Know, Physical Activity for the Prevention of CVDs, Overweight and Obesity, Smoking as a Risk Factor for CVDs, Hypertension: Diagnosis, Hypertension: Treatment, Myocardial Infarction: Diagnosis and Treatment. At Stage 2 a total of 125 participants were randomly selected and assigned into one of the four training groups depending on the training mode, i.e. text posts of up to 4.000 characters, short video clips of up to 5 minutes, text posts followed by video clips or video clips followed by text posts in Group 1 (n=31), Group 2 (n=31), Group 3 (n=33) and Group 4 (n=30), respectively. Before and after training respondents in all the four groups completed the Heart Disease Knowledge Questionnaire (HDKQ). Results: The total number of people who listened to and read the materials of the online school was 2.108 people; the overall engagement (comments, shares and saves) was 1.598 people. The average percentage viewed was 22%. The online school audience was mostly female (84%). A total of 80.8% of participants had post-secondary education. The mean duration of hypertension was 6.1 years. Smokers accounted for 3.2% of the respondents. Before training the number of correct responses for 29 HDKQ statements was 18.4 (CI, 17.5;19.4), with no significant differences between the groups. After training the number of correct responses increased to 21.9 (CI, 21;22.7) (p (ANOVA) <0.0001). The post-hoc analysis showed that after training the respondents from Group 3 gave the lowest number of correct responses compared to Groups 1 and 2, i.e. Δ=4.9 (CI, -7.8;2.0) and Δ=3.7 (CI, -6.5;-0.8), respectively. Participants from Group 4 had more correct responses than the respondents in Group 3, i.e. Δ=5.2 (CI, 2.2;8.1). The regression analysis showed that the post-training number of correct responses in Group 4 increased on average by 3.9 compared to Group 3 (β=3.94 p=0.04 (CI, 0.21;7.66)). The study showed a significant association between the duration of hypertension and the number of correct responses both before and after training (β=0.20 p=0.007 (CI, 0.06;0.34) and β=0.16 p=0.005 (CI, 0.05;0.27), respectively). No association was found between gender, age, education and the number of correct responses both before and after training. Conclusions: In all the 4 groups there was a tendency to increase in the number of correct responses after training, but among the training modes the most effective method of informing people about the primary prevention of hypertension using a social media website corresponded to the following sequence: a video clip of up to 5 minutes followed by a text post of up to 4,000 characters. Participants in Group 3 who received the material in the form of text posts followed by video clips gave the lowest number of correct responses for HDKQ statements after training. The results of this study can be used to design online training programmes for the primary prevention of hypertension.
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